Workshop - Legal and Ethical Challenges for Driverless Cars and Smart Roads (October 2017)

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Slide Presentation at Bath Digital Festival

Chris Connolly
October 2017, Bath Digital Festival (United Kingdom)
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[Download presentation slides (PDF) »]


  • Driverless cars
    • Level 4 and Level 5 on the autonomous vehicle scale - no driver at all, with a computer making all decisions once a navigation target and some basic rules are set
  • Smart roads
    • Road networks that interact with all vehicles and road infrastructure (traffic lights, speed limits etc.)
    • Most vehicles from 2018 will be fitted with an automatic transponder and older vehicles can be retro-fitted
    • Modern roads have some smart infrastructure built in - more on the way
  • Driverless cars and smart roads are a rapidly emerging technology
    • The law is famously poor at keeping up with new technology

Top 6 Legal and Ethical Challenges

  • 1. Privacy
  • 2. Safety and Selection
  • 3. Liability
  • 4. Cultural Differences
  • 5. Traffic Priorities
  • 6. Trust

1. Privacy

  • Constant broadcast
    • A typical transponder broadcasts vehicle type and make, speed, braking, acceleration, indicators etc.
    • The transponder is identified by a signed digital certificate (to avoid fraud and impersonation)
  • Access requests
    • Requests will be common for both live and historical movement and location data - from law enforcement, lawyers in civil disputes, general traffic management etc.
  • Privacy law
    • Privacy law currently relies on notice and consent (difficult for vehicles) and in any case provides huge exceptions for law enforcement, emergencies etc.
  • Privacy by design
    • A Privacy Impact Assessment can often identify solutions - for example, in one ‘privacy friendly’ option a bundle of certificates for each transponder can be randomly shuffled

2. Selection

  • Safety and selection
    • Often called ‘The Trolley Problem’ - where an accident resulting in a fatality is unavoidable, how do you decide who should die?
    • You can even ‘play’ a game based on the Trolley Problem at MIT:
  • Case study: Germany (Guidelines 2017)
    • Self-driving cars must prioritise human life over property and animals.
    • Self-driving cars must do the least amount of harm if put into a situation where hitting a human is unavoidable
    • Self-driving cars must not discriminate based on age, gender, race, disability, or any other observable factors.

3. Liability

  • Overview
    • A common approach to determining liability is to assess which party has the greatest ability to avoid damage. A supplementary test is which party has the greatest ability to compensate for any damage
  • Vehicle manufacturers
    • In order to build confidence in driverless cars, some manufacturers have offered an indemnity for any damage (but check the fine print!)
    • Manufacturers are unlikely to be able to avoid liability for any damage resulting from their negligence in design or implementation (due to consumer protection laws - but these laws differ from country to country)
  • Owners
    • Owners may be pressured to accept some liability (e.g. in contracts). There are protections against unfair contract terms in the UK.
  • Insurance
    • Compulsory insurance is likely to be the long term solution to liability issues for driverless cars - the manufacturer indemnities are more akin to an introductory offer or stunt

4. Cultural Differences

  • Driving is cultural
    • More than just the left / right divide - there are numerous national and regional differences in driving behavior and traffic management
    • Most approaches are based on customs or etiquette, but some are enshrined in law
  • Managing cultural differences
    • This will be challenging if algorithms for driverless cars are developed in just a handful of jurisdictions, or if AI is based on data initially obtained from just one culture.
    • Recent developments in AI have demonstrated an ability for AI to develop new knowledge itself, raising questions about ‘who is really in charge’.
    • The most difficult phase will be when driverless cars and traditional cars have to share limited road space

5. Priorities

  • Smart roads will have the ability to prioritise specific vehicles and manage overall traffic patterns
    • General recognition that emergency vehicles will receive priority from driverless cars and smart road infrastructure (e.g, traffic signals)
    • Some successful pilots of smart roads allowing individual heavy goods vehicles (and convoys) to reach a destination with minimal stopping (reduces environmental impact and road maintenance)
  • Who determines these priorities?
    • Significant potential for conflict, bias and influence
    • Potential for entrenching privilege / disadvantage
  • AI and priorities
    • In one AI experiment the AI becomes more aggressive as the challenge becomes more competitive

6. Trust

  • Trust is a key issue when you are relying on an algorithm to make key decisions
    • Users may not be able to see or understand the details of the algorithm
    • The algorithm may make selections or priorities without the consumer being aware
  • Trust in the vehicle / transport sector is in crisis
    • Many industry players are ‘disrupters’ who have gone to great lengths to avoid or undermine regulation
  • For example, Uber is a leading player in the driverless car sector. They have been the subject of a series of controversies, including:
    • Two major privacy breaches where senior management directed staff to place ‘opponents’ (journalists) under surveillance and even directly threatened journalists with revealing their personal data
    • Revelations that Uber had developed and used specific software (Greyball) to identify and avoid regulatory staff (e.g. inspectors)
  • Numerous vehicle manufacturers have also been caught up in the emissions testing fraud scandal


  • Overall, driverless cars and smart roads have the potential to deliver significant benefits
    • Driverless cars are not affected by fatigue, alcohol, health conditions and distractions
    • Smart roads and transponders allow vehicles to ‘see’ traffic hidden by hills, corners, fog, snow and blinding light
    • Traffic management and vehicle priority (e.g. emergency vehicles) are enhanced by smart roads and transponders
  • However, key issues will require careful management, including direct intervention and regulation
  • AI and algorithms need to be transparent and subject to rules and restraints
  • The core approach should be:
    • “Even if there is no driver behind the wheel, a human is always in charge”

Further information

[Download presentation slides (PDF) »]

Chris Connolly
October 2017, Bath Digital Festival (United Kingdom)
Read more »

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